Digital Subscriber Line (DSL) technology greatly increases the digital capacity of an ordinary telephone line, allowing much more information to be channeled into a home or office. The speed that a DSL modem can achieve is based on the distance between the home or office and the central office. Symmetric DSL (SDSL) utilizes a single twisted pair and is typically used for short connections that need high speed in both directions. High Bit Rate DSL (HDSL) is a symmetric technology that uses two cable pairs and may achieve usable transmission to 12,000 feet. Each twisted pair may be used to provide T1 transmission, but the lines may not be shared with analog phones. HDSL-2 needs only one cable pair and supports a distance of 18,000 feet. SDSL utilizes only one cable pair and may be used with adaptive rates from 144 Kbps to 1.5 Mbps. The DSL technology provides “always-on” operation.
Asymmetric DSL (ADSL), which uses frequencies that are higher than voice, shares telephone lines and may be used to access the Internet. For ADSL, a Plain Old Telephone System (POTS) splitter generally must be installed at the user end to separate the voice frequencies and the ADSL frequencies. The G.lite version of ADSL, also known as the ADSL lite, Universal ADSL or splitterless ADSL, gets around the splitter requirement by having all phones plug into low-pass filters that remove the ADSL high frequencies from the voice transmissions. ADSL is available in two modulation schemes: the Discrete Multi-tone (DMT) or Carrierless Amplitude Phase (CAP).
In DMT-based DSL modems, the selected bandwidth of 1.104 MHz is divided into bins and the data bits are used for Quadrature Amplitude Modulation in each bin. During the initialization period, a channel SNR estimation phase is employed to transmit a known pseudo-random noise (PRN) sequence while the receiver computes the channel characteristics from the received signal. The characteristics are computed in the form of a gk·Nk−1 ratio, where gk is the channel gain (attenuation, |H(k)|2) in frequency band k, and Nk is the noise power in band k. Prior art has disclosed a number of algorithms for determining the power distribution across the full frequency bandwidth for maximum data rate. The optimum approach for Additive White Gaussian Noise (AWGN), has been proved to be a ‘water pouring’ algorithm of power distribution, where the gk·Nk−1 profile is considered to be equivalent to the ‘terrain’ and the available power budget is likened to ‘water that is poured’ on the terrain. In this analogy, the water depth at position k is equivalent to the power allocated to the frequency bin k.
The following analysis provides a brief description of this approach. As is known to those skilled in the art, the relationship between the number of bits in a frequency bin and the power needed to transmit that number of bits, for a specified bit error rate (BER) at the receiver for which gk·Nk−1 is the measured channel characteristic, is given by the following expression:
                                                                        b                k                            =                                                log                  2                                ⁡                                  [                                      1                    +                                                                  3                        ·                                                  g                          k                          ′                                                ·                                                  E                          k                                                                                            K                        ·                                                  (                                                      N                            k                                                    )                                                                                                      ]                                                                                        k              =                              1                ⁢                …256                                                                        Eq        .                                  ⁢        1            wherebk=No. of bits in frequency bin kEk=Power required in bin k to transmit the bk bits
            g      k      ′              N      k        =      Measured    ⁢                  ⁢    channel    ⁢                  ⁢    attenuation    ⁢                  ⁢    to    ⁢                  ⁢    noise    ⁢                  ⁢    power    ⁢                  ⁢    ratio    ⁢                  ⁢    in    ⁢                  ⁢    bin    ⁢                  ⁢    k  Nk=Noise power in bin k
  K  =            [                        Q                      -            1                          ⁡                  (                                    P              e                                      N              e                                )                    ]        2  where
  2  ≤      [                  N        e            =              4        ·                  (                      1            -                          1                                                2                                      b                    k                                                                                )                      ]    ≤      4    ⁢                  ⁢    for    ⁢                  ⁢    2    ≤      b    k  Given the expression in Eq. 1, the power needed to transmit bk bits in bin k can be obtained by inverting the expression by ignoring the dependence of Ne on bk. Prior art has shown that approximating Ne by a constant between 2 and 4 has a negligible effect on the overall data capacity.)
      E    k    =                    KN                  g          k          ′                    ⁢              (                              2                          b              k                                -          1                )              =                  N                  g          k                    ⁢              (                              2                          b              k                                -          1                )            where
      g    k    =            3      ⁢              g        ′              K  The problem of power allocation consists of distributing the available power budget over the 256-bins so that the capacity as defined by
      ∑          k      =      1        256    ⁢          ⁢      b    k  is maximized. The allocation must be performed within constraints of the DSL modems that are subject to a power mask constraint that limits the maximum power that may be allocated to each bin.
The solution to the 2-tone power allocation problem is known in the art. The available power is distributed optimally over two bins to maximize the 2-bin capacity of b1+b2. In order to perform the 256-bin power allocation, the prior art proposes an iterative approach to solve the “water-pouring” problem. However, such a solution for the 256-bin power allocation results in noisy bins. Thus, there is a need for a method, system and computer medium for assigning data bits to bins for simplex transmission while minimizing noise.